Method and system for dynamically managing staffing agencies and recruiters in a vms system

ABSTRACT

A computer-implemented method for dynamically matching clients with suppliers based on cloud environment, the method comprising: allowing each client to run as their own instance in a shared environment through an application; providing an interface for each client to publish their open jobs to a network of suppliers through the same application; providing an interface for suppliers to add talent into the ecosystem, and dynamically matching a job of the client to a network of suppliers and talent within the ecosystem as each supplier adds talent into the system.

TECHNICAL FIELD

The present disclosure relates to systems and methods for hiring and management, and more particularly to a method and system for dynamically matching businesses and talent pools.

BACKGROUND OF THE DISCLOSURE

In traditional systems, a business can only connect with its own contracted vendors and the contract vendor's talent pool. This causes an inherent limit to the candidates that the business has access to, making it cumbersome and expensive to hire talent. Often, if the existing suppliers are not able to fulfill any of the open jobs distributed by the business, the business must go and find additional suppliers to work with them. This is a long and tedious process that requires vetting of the supplier, their capabilities, agreeing upon legal and commercial terms, obtaining the supplier's business documents, including certificates of insurance, and more. This process is burdensome, takes weeks if not months to complete, and delays the ability for the business to hire until the process is complete. Additionally, even after all this effort, there is no guarantee that the supplier will be successful in fulfilling the job by presenting suitable candidates that the business can hire, which means the business may be forced to repeat this process to find additional suppliers by starting the supplier search and onboarding process from scratch.

In the typical process, when suppliers join the program, any candidates they submit are only visible to that one business and cannot be submitted to one or more jobs belonging to different clients. Each supplier must conduct business development efforts to join as many client hiring programs as possible, which means the sales effort is an ongoing process. This creates extensive inefficiencies in the process, is difficult to manage, and can increase program management costs. Thus, there exists a need in the art to address the inefficiencies and problems described above.

SUMMARY OF THE DISCLOSURE

Embodiments of the present disclosure provides novel methods for vendor management and hiring based on a shared and open network ecosystem approach. Embodiments of the present disclosure provide systems and methods to connect businesses that are seeking talent with a network of talent suppliers/vendors, and talent pools. It can be appreciated that this provides greatly increased efficiency for the businesses that are looking to hire.

In one aspect, a non-transitory computer-readable medium is provided. The non-transitory computer-readable medium stores instructions that, when executed by a computing device, cause the computing device to perform a method. The method includes dynamically matching clients with suppliers based on cloud environment, the method comprising: allowing each client to run as their own instance in a shared environment through an application; providing an interface for each client to publish their open jobs to a network of suppliers through the same application; providing an interface for suppliers to add talent into the ecosystem, and dynamically matching each talent record with all client jobs within the ecosystem as each supplier adds talent into the system.

Although specific advantages have been enumerated above, various embodiments may include some, none, or all of the enumerated advantages. Additionally, other technical advantages may become readily apparent to one of ordinary skill in the art after review of the following figures and description.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present disclosure and its advantages, reference is now made to the following description taken in conjunction with the accompanying drawings, in which like reference numerals represent like parts.

FIG. 1 illustrates an architecture diagram of an exemplary VMS system according to an embodiment of the present invention.

FIG. 2 illustrates a block diagram of an exemplary computing device according to an embodiment of the present invention.

FIG. 3 illustrates an exemplary method of dynamically matching according to an embodiment of the present invention.

FIG. 4 illustrates an exemplary method of a implementing a digital right-to-represent embodiment of the present invention.

FIG. 5 illustrates an exemplary system for dynamically matching according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE DISCLOSURE

It should be understood at the outset that, although exemplary embodiments are illustrated in the figures and described below, the principles of the present disclosure may be implemented using other techniques. The present disclosure should in no way be explicitly limited to the exemplary implementations and techniques illustrated in the drawings and described below. Additionally, unless otherwise specifically noted, articles depicted in the drawings are not necessarily drawn to scale.

The present disclosure is directed towards workforce management systems and methods to improve hiring outcomes and speed up time-to-hire. Embodiments of the present disclosure are directed towards a VMS network that helps businesses manage their workforce and improve their hiring outcomes. Methods of direct sourcing are provided for enabling access to talent pools and improving hiring speed and efficiency. In a further embodiment of the present disclosure, the VMS network is fully integrated with a crowd staffing process to deliver novel results. In one embodiment, a web-based software application running on a server hosts a marketplace that brings businesses, talent suppliers, and candidates into a common ecosystem to conduct work, collaborate, and deliver targeted outcomes. On demand talent pools provide the ability to speed up time-to-hire and connect businesses with a wide range of talent in a cloud-based marketplace.

According to a further embodiment, the present disclosure provides a web-based software VMS application running on a server that is networked in a cloud-based system, which means that all jobs, talent suppliers and talent pools are part of a shared and open environment. It can be appreciated that this enables many-to-many matching for businesses, and publishing of jobs to a larger network of talent suppliers and talent pools. This is unlike standard VMS systems that are closed silos, which means that in these standard systems jobs can only be published to known suppliers and talent pools of a particular client. According to one embodiment, jobs can only be published to known suppliers and matched against candidates of a particular client's talent pool.

Embodiments of the present disclosure further provide a core technology architecture that allows the system to be setup in a multi-tenancy cloud-hosted environment. According to one embodiment of the present disclosure, each client is allowed to run as their own instance in a shared environment through a web-based application. According to this embodiment, a client can manage their incumbent suppliers as well as publish their open jobs to a network of suppliers through the same application. This provides the client extensive reach into a network of talent suppliers that can support them in filling their open jobs quickly and easily.

According to a further embodiment of the present disclosure, as each supplier adds talent into the system, that talent can also be matched to other clients within the ecosystem. It can be appreciated that this embodiment provides exponential access to finding suitable jobs for each candidate as each provider adds talent into the system.

Referring now to the figures in more detail, FIG. 1 illustrates an architecture diagram of an exemplary dynamically matching VMS system 100 according to an embodiment of the present invention. A multidirectional Matching Engine 111 connects to Talent Suppliers 102, Candidates 106, and Jobs 108 across an ecosystem. Talent Suppliers 101 may consist of recruiters or other providers of strategic supply chain talent. Jobs 108 may be managed by Hiring Managers or other parties seeking to hire for jobs. Via the Matching Engine 111, Jobs 108 are multi directionally matched with Candidates 106, Jobs 108 with Talent Suppliers 102, and Candidates 106 with Talent in all directions. In a further embodiment, Matching Engine 111 distributes Jobs 102 to the most capable, proven suppliers based on predetermined job priority. In a further embodiment, Matching Engine 111 dynamically distributes to optimal number of qualified suppliers based on successful hires in the recent past, supplier bandwidth, skills, and geographical expertise.

The dynamically matching VMS system 100 including Matching Engine 111 is typically implemented on a computing device, such as a server. FIG. 2 illustrates a block diagram of an exemplary computing device 200 according to an embodiment of the present invention. The computing device 200 can be used to execute commands such as caching, storing, computing, transferring, sending, receiving and/or displaying information. According to an embodiment of the present disclosure, Matching Engine 111 utilizes Artificial Intelligence configured to match jobs both to the best Talent Suppliers and to the best Candidates in their talent pools. According to an embodiment, Matching Engine 111 uses an Artificial Intelligence integrating targeted metrics to determine which recruiters are best positioned to staff each position and which candidates are likely to excel in each position and considers both the candidate and the employer to ensure that everyone will be satisfied with the match. An example of this process is outlined below.

First, the process compares a candidate's entire resume to each open job, checking the relevancy of their experience and skills against the roles' requirements. According to an embodiment, these requirements include industry experience, hard skills, keywords, and more. This provides a baseline match to ensure that the candidate has the necessary background to be qualified for a job.

Then, the process utilizes built-in AI that uses natural language processing to “read” a candidate's resume and determine whether it's a good fit for the open role. It can be appreciated that this saves a lot of time as this is a time-consuming task for recruiters.

Next, the process considers each candidates' proximity to the job location. By automatically narrowing down a list of qualified, available, and nearby candidates, the process frees up Talent Suppliers from screening tasks so they can use their time to help great candidates through the hiring process.

According to an embodiment, once a job has been published to the VMS, the platform analyzes its unique elements and success factors, benchmarking it against similar jobs. The Job Matching Engine first uses this information to identify potential candidates from within the existing Talent Pool and alerts the hiring managers if there are matches. Simultaneously, the Matching Engine 111 identifies the best staffing vendors to service the requisition based on their past performance with similar jobs and their current capacity, ensuring that staffing vendors with the right experience and bandwidth are working on the jobs.

According to a further embodiment, working in tandem with the Matching Engine 111 is a Job Distribution Engine. The Job Distribution Engine uses the staffing vendors' past performance (including which job requisitions they received, saved, and submit qualified candidates to) concurrently with benchmarking against similar jobs across the program with the concept of capacity (how many open job requisitions can a vendor effectively support) to notify and invite the appropriate Talent Suppliers to each job.

The Job Distribution Engine also mitigates hotspots—jobs receiving attention from too many recruiters while other jobs go neglected—by monitoring all open jobs, measuring vendor activity, and tracking Key Performance Indicators (KPIs) at every stage of the hiring process. When KPIs, such as submission-to-hire, are met, surpassed, or missed entirely, the Job Distribution Engine re-prioritizes jobs to ensure that the right staffing vendors' attention will be given to the right jobs at the right time.

FIG. 2 illustrates a hardware structure suitable for implementing a computing device 200. FIG. 2 illustrates a processor 202 coupled to a bus 204. Also coupled to the bus 204 are a memory 206, a storage device 208, a keyboard 210, a graphics adapter 212, a pointing device 214, and a network adapter 216. A display 218 is coupled to the graphics adapter 212.

FIG. 3 illustrates a dynamic process for matching businesses with suppliers in real time according to an embodiment of the present disclosure. In one embodiment, the system automatically matches suitable jobs and suppliers in real time based on a dynamic process. The process matches jobs with candidates, jobs with suppliers, and candidates with suppliers (all directions) in real-time across the marketplace. First, at step 302, talent suppliers apply via client-branded registration page. Next, at step 304, the system validates supplier capabilities. Next, the system builds relationships and adds suppliers to the hiring marketplace in step 306. In step 308, real time dynamic matching of jobs to the best suppliers is done. New talent suppliers can apply in step 310. At step 312, hires are made from more suppliers and a larger overall talent pool. In a further embodiment, the process matches in real-time based on one or more of the following traits: Prior Success, Skills, Job Priority, Geographic Expertise, and Talent Supplier Bandwidth. According to a further embodiment, a recruiter's bandwidth is determined by their workload of open jobs. It can be appreciated that this provides for more efficient engagement with suppliers such that the right roles are tilled at the right time.

FIG. 4 illustrates a digital right-to-represent according to an embodiment of the present disclosure. According to an embodiment, the system offers a recruiter a right to represent a represented candidate, wherein the system only allows that recruiter to submit the represented candidate's application. According to an embodiment, the right-to-represent is completely digital and is placed within the system vendor management system (VMS) and is required of every submitted candidate for every open job.

According to this embodiment, the right to represent is done digitally and for every position a candidate is submitted for. It can be appreciated that this solves the problem of recruiters not being rewarded for the hire, eliminates duplicate submissions, and allows the candidates to choose the recruiter that represents them.

According to a further embodiment, by making the entire right to represent process digital, the system and process records time stamps and IP addresses which makes it difficult for a candidate to be misrepresented or represented multiple times. In this way, candidates can ensure that they oversee their own job hunt and that they want to be represented by this Talent Supplier/Agency for this job. It can be appreciated that this saves time and effort by preventing each candidates' application from being submitted by multiple agencies (which clutters the list of viable candidates with duplicates). According to this embodiment, candidates can only be submitted once, which provides list of quality candidates without duplicates.

A process illustrating a digital right to represent is disclosed in FIG. 4 . First, in step 402, one or more recruiters invite a qualified candidate to apply for the open job. Next, in step 404, the candidate then logs into the platform to review position specific details. Next, in step 406, the candidate declares whether they're interested and, if so, whether they want to be represented by the recruiter who invited them to apply. If multiple recruiters invite them, candidates are prompted to choose within the system which recruiter they would like to go with. Next, once the recruiter has been chosen, the system provides real time tracking of supplier representation in step 408

Next, once a candidate has accepted an invitation to be submitted for an open position, they digitally grant their recruiter the right to represent in step 410. As this a required step in the process, there's never confusion around which recruiter represents each candidate. According to this embodiment, candidates have full control over whom they work with and for which jobs they're submitted, and recruiters don't waste their time pursuing candidates who are already submitted. It can be appreciated that with this process hiring companies no longer have to battle with recruiters over who submitted a candidate or work from a list that includes duplicate candidates. Next, in step 412, according to an embodiment in this step of a candidate's process of opting in to join a client's talent community and a global talent network, the system matches them to any and all jobs in our ecosystem across all clients.

As part of the digital right to represent process, the candidate can elect to join the client's talent community. This allows the candidate to receive updates from the client about new jobs that may be applicable to the candidate. Simultaneously, the candidate can also elect to join the System's global talent network. This allows the candidate to receive job notifications about any matching jobs across all System clients.

FIG. 5 illustrates an exemplary system for dynamically matching according to an embodiment of the present invention. FIG. 5 discloses Robotic Process Automation 502, Artificial Intelligence and Machine Learning 504, Business Logic 506, and Workflow Management 508 modules fed into a Hiring Pipeline 510. Hiring Managers 512, Staffing Vendors 514, and Candidates 516 are bi-directionally connected to Hiring Pipeline 510. According to an embodiment, the Robotic Process Automation 502 module further comprises providing notifications and invitations. According to a further embodiment, Robotic Process Automation 502 further comprises providing tracking and reporting. According to an embodiment, Artificial Intelligence and Machine Learning 504 module further comprises providing data analysis, pattern recognition, and correlation as well as optimization algorithms. According to an embodiment, the Business Logic 506 further comprises business rules and validation, and action and alerts. According to an embodiment, the Workflow Management 508 module further comprises event scheduling and coordination, as well as task management.

Some portions of the preceding detailed descriptions have been presented in terms of Software Engines and symbolic representations of operations on data bits within a computer memory. These descriptions and representations are the ways used by those skilled in the data processing arts to convey the substance of their work effectively to others skilled in the art. An Algorithm or Software Engine is here, and generally, conceived to be a self-consistent sequence of operations leading to a desired result. The operations are those requiring physical manipulations of physical quantities.

It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise as apparent from the above discussion, it is appreciated that throughout the description, discussions utilizing terms such as those set forth in the claims below, refer to the action and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical (electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices.

The techniques shown in the figures can be implemented using code and data stored and executed on one or more electronic devices. Such electronic devices store and communicate (internally and/or with other electronic devices over a network) code and data using computer-readable media, such as non-transitory computer-readable storage media (e.g., magnetic disks; optical disks; random access memory; read only memory; flash memory devices; phase-change memory) and transitory computer-readable transmission media (e.g., electrical, optical, acoustical or other form of propagated signals—such as carrier waves, infrared signals, digital signals).

Modifications, additions, or omissions may be made to the systems, apparatuses, and/or methods described herein without departing from the scope of the disclosure. For example, various components of the systems and apparatuses may be integrated or separated. Moreover, the operations of the systems and apparatuses disclosed herein may be performed by more, fewer, or other components and the methods described may include more, fewer, or other steps. Additionally, steps may be performed in any suitable order. As used in this document, “each” refers to each member of a set or each member of a subset of a set.

The processes or methods depicted in the preceding figures may be performed by processing logic that comprises hardware (e.g., circuitry, dedicated logic, etc.), firmware, software (e.g., embodied on a non-transitory computer readable medium), or a combination of both. Although the processes or methods are described above in terms of some sequential operations, it should be appreciated that some of the operations described may be performed in a different order. Moreover, some operations may be performed in parallel rather than sequentially.

In the foregoing specification, embodiments of the invention have been described with reference to specific exemplary embodiments thereof. It will be evident that various modifications may be made thereto without departing from the broader spirit and scope of the invention as set forth in the following claims. The specification and drawings are, accordingly, to be regarded in an illustrative sense rather than a restrictive sense.

To aid the Patent Office and any readers of any patent issued on this application in interpreting the claims appended hereto, applicants wish to note that they do not intend any of the appended claims or claim elements to invoke 35 U.S.C. § 112(f) unless the words “means for” or “step for” are explicitly used in the particular claim. 

1. A computer-implemented method for dynamically matching clients with suppliers based on cloud environment, the method comprising: allowing a client or a plurality of clients to run as their own instance in a shared environment through an application; providing an interface for the client to publish one or more open jobs to a network of suppliers through the application; providing a second interface for a plurality of suppliers to add talent into the shared environment; and dynamically matching a job of the client to the plurality of suppliers and talent within the shared environment as each supplier adds talent into the system.
 2. The computer-implemented method of claim 1, wherein dynamic matching is based on profile, performance, and the pools of talent that each supplier represents.
 3. The computer-implemented method of claim 1, further comprising determining which suppliers to invite to which job in the shared environment.
 4. The computer-implemented method of claim 2, further comprising solution allowing candidates to select the talent supplier they prefer to work with.
 5. The computer-implemented method of claim 3, further comprising eliminating duplicate candidate submissions and increasing transparency.
 6. The method of claim 5, further providing a digital right to represent.
 7. The method of claim 5, further comprising allowing a candidate to join a talent community of the client and a global talent network via a third interface.
 8. A system, comprising: a dynamically matching engine processor, comprising: a processor a non-volatile data store comprising data and software modules; and an electronic communication interface comprising an input and output; the software modules, when executed by the processor, causing the dynamically matching engine processor to: allow a client or a plurality of clients to run as their own instance in a shared environment through an application; provide an interface for the client to publish their open jobs to a network of suppliers through the same application; provide a second interface for a plurality of suppliers to add talent into the shared environment; and dynamically match a job of the client to the plurality of suppliers within the shared environment as each supplier adds talent into the system.
 9. The system of claim 8, wherein the dynamic matching is based on profile, performance, and the pools of talent that each supplier represents.
 10. The system of claim 8 wherein the matching engine processor is further configured to: determine which suppliers to invite to which job in the shared environment inviting new suppliers into the shared environment.
 11. The system of claim 8 wherein the matching engine processor is further configured to: allow candidates to select the talent supplier they prefer to work with.
 12. The system of claim 8 wherein the matching engine processor is further configured to: eliminate duplicate candidate submissions and increasing transparency.
 13. The system of claim 8, further providing a digital right to represent.
 14. The system of claim 8, further comprising allowing a candidate to join a talent community of the client and a global talent network via a third interface. 